Platform Expert - Senior

at  CAPGEMINI ENGINEERING

SENIOR PLATFORM EXPERT (LISBON)

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

Proficiency in Azure Machine Learning: The candidate should be proficient with Azure Machine Learning platform, including creating and managing workspaces, experiments, compute resources, and datasets. Experience with Azure Databricks: The candidate should have experience with Azure Databricks for big data analytics. This includes knowledge of creating Databricks workspaces, clusters, notebooks, jobs, and tables. Knowledge of Machine Learning and Data Science: A strong understanding of machine learning algorithms and data science concepts is necessary. This includes data cleaning, preprocessing, feature engineering, model training, and evaluation. Experience with Spark: Experience with Spark for big data processing is important. This includes knowledge of Spark SQL, DataFrames, and MLlib.
Familiarity with Azure Services: The candidate should be familiar with other Azure services that can be integrated with Azure Machine Learning and Databricks, such as Azure Data Factory, Azure Synapse Analytics, Azure Storage, etc. Cloud Computing: Deep understanding of cloud computing concepts, including virtual machines, containers, serverless computing, and cloud storage. Experience with Machine Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, Keras, etc., is important. Familiarity with MLOps Tools: Experience with tools like Kubeflow, MLflow, TFX, Seldon, etc., that help in the deployment, monitoring, and maintenance of machine learning models. Knowledge of DevOps Practices: Understanding of DevOps practices like CI/CD is important. Familiarity with GitHub and Azure DevOps would be a plus.
Soft Skills: Good communication skills to explain complex concepts to non-technical stakeholders, problem-solving skills, and ability to work in a team are also important.
The following deliverables should be considered for this position:
Technical guidelines
Code Reviews
Reference architectures
Development blueprints.
Solution analysis documentation
Technical architecture solutions documentation
Decision support material